The ocean’s meso- and submeso-scales (1-100 km, days to weeks) host features like filaments and eddies that have a key structuring effect on phytoplankton distribution, but that due to their ephemeral nature, are challenging to observe. This problem is exacerbated in regions with heavy cloud coverage and/or difficult access like the Southern Ocean, where observations of phytoplankton distribution by satellite are sparse, manned campaigns costly, and automated devices limited by power consumption. Here, we address this issue by considering high-resolution in-situ data from 18 bio-logging devices deployed on southern elephant seals (Mirounga leonina) in the Kerguelen Islands between 2018 and 2020. These devices have submesoscale-resolving capabilities of light profiles due to the high spatio-temporal frequency of the animals’ dives (on average 1.1 +-0.6 km between consecutive dives, up to 60 dives per day), but observations of fluorescence are much coarser due to power constraints. Furthermore, the chlorophyll a concentrations derived from the (uncalibrated) bio-logging devices’ fluorescence sensors lack a common benchmark to properly qualify the data and allow comparisons of observations. By proposing a method based on functional data analysis, we show that a reliable predictor of chlorophyll a concentration can be constructed from light profiles (14 686 in our study) and matchups with satellite ocean-color data, thus enabling effective (1) homogenization then calibration of the bio-logging devices’ fluorescence data and (2) filling of the spatial gaps in coarse-grained fluorescence sampling. The developed method improves the spatial resolution of the chlorophyll a field description from ~30 km to ~12 km. These results open the way to empirical study of the coupling between physical forcing and biological response at submesoscale in the Southern Ocean, especially useful in the context of upcoming high-resolution ocean-circulation satellite missions like SWOT. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications.

MARLEY (Monitoring deep-seA coRaL EcosYstems) is a deep seafloor observing system dedicated to the monitoring of cold-water coral habitats. The system is deployed in the Lampaul canyon off Brittany, France since August 2021 and maintained each year during the ChEReef-Obs cruises. The study site is a coral garden dominated by Madrepora oculata, located on a sedimented platform at 780 m depth. MARLEY is equipped with a CTD SBE 37-SIP, an oxygen optode Aanderaa (4330 or 4831), an ADCP Teledyne RDI Workhorse 300kHz, a turbidity sensor Wetlabs ECO NTU (sensitivity: 0-1000 NTU), a sediment trap Technicap PPS 4/3 – 24 bottles and a camera module. The camera module, which can be moved from up to 30 m from the main station, is equipped with a camera AXIS Q1786, two flash lights and a fluorometer & scattering meter SEA-BIRD ECO FLNTU. All sensors are controlled and synchronised by the Communication and Storage Front-end - 2nd generation (COSTOF2), which is also managing data storage. Optical sensors are protected from fouling by electrochlorination (20 seconds, each 6 hours). The oxygen optode is calibrated each year prior to deployment. These datasets provide raw data from the oxygen optode Aandera 4831, the CTD Seabird SBE37, the Wetlabs ECO NTU and the SEAR-BIRD ECO FLNTU covering the period 28/08/2021 to 19/01/2022, with a frequency of 15 minutes. Data from Wetlabs ECO NTU include raw counts and Nephelometric Turbidity Unit (NTU) derived from manufacturer’s calibration with Scale Factor = 0.0611 and Dark Counts = 50. Data form SEABIRD ECO FLNTU include raw counts at 695 nm (Chlorophyll) and 700 nm (Turbidity). Chlorophyll concentration (µg/l) is derived from manufacturer’s calibration with Scale Factor = 0.0180 and Dark Counts = 48. Nephelometric Turbidity Unit (NTU) is derived from manufacturer’s calibration with Scale Factor = 0.0481 and Dark Counts = 50. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications.

The Green Edge project was designed to investigate the onset, life and fate of a phytoplankton spring bloom (PSB) in the Arctic Ocean. The lengthening of the ice-free period and the warming of seawater, amongst other factors, have induced major changes in arctic ocean biology over the last decades. Because the PSB is at the base of the Arctic Ocean food chain, it is crucial to understand how changes in the arctic environment will affect it. Green Edge was a large multidisciplinary collaborative project bringing researchers and technicians from 28 different institutions in seven countries, together aiming at understanding these changes and their impacts on the future. The fieldwork for the Green Edge project took place over two years (2015 and 2016) and was carried out from both an ice camp and a research vessel in the Baffin Bay, Canadian arctic. Here, we describe the data set obtained during the research cruise, which took place aboard the Canadian Coast Guard Ship (CCGS) Amundsen in spring 2016. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications.

Several sea trials with the newly developed CO2 Seaglider in the Gulf of Alaska and data evaluation with discrete water and underway samples suggest near ‘weather quality’ CO2 data as defined by the Global Ocean Acidification Network. This data set describes one such data set from the CO2 Seaglider, in February of 2023. Please see publication by the same authors at https://doi.org/10.5194/egusphere-2024-1055. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications.

Several sea trials with the newly developed CO2 Seaglider in the Gulf of Alaska and data evaluation with discrete water and underway samples suggest near ‘weather quality’ CO2 data as defined by the Global Ocean Acidification Network. This data set describes one such data set from the CO2 Seaglider, in May of 2022. Please see publication by the same authors at https://doi.org/10.5194/egusphere-2024-1055. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications.

Region: Varna lakes (Black Sea) Period of observation: 2022 Type of measurements: data from water column profiling

Region: Varna lakes (Black Sea) Period of observation: 2023 Type of measurements: data from water column profiling

Region: Varna lakes (Black Sea) Period of observation: 2023 Type of measurements: data from water column profiling

The RESILIENCE experiment took place in April and May 2022 on the R/V Marion Dufresne in the Southwestern Indian Ocean, South of the Mozambique Chanel and offshore of Durban (South Africa). The main scientific objective was to study the interaction at fine scale (about 10km) between physics and biology. To do so CTD stations were performed accompanied by MVP profiles, measuring temperature, conductivity (hence salinity) and fluorescence. The MVP is performing profiles downward in a free-fall mode and upward, towed by a cable. This instrument is subject to many errors. Here we have first corrected the sensors offset between the CTD and MVP. Second, we have also corrected the thermistor viscous heating and the thermal lag between the thermistor and the conductivity cell. Third, we have corrected the thermal mass error on the lowering profiles. Only temperature and conductivity/salinity measurements are corrected. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications.

Region: Varna lakes (Black Sea) Period of observation: 2022 Type of measurements: data from water column profiling